Reputation: 211
I have a raw input csv data where all the fields are of string type. I want to convert this csv to parquet format. However on conversion to parquet I want to write it by providing a custom schema to the data. I am using PyArrow for csv to parquet conversion.
How can I provide a custom schema while writing the file to parquet using PyArrow?
Here is the code I used:
import pyarrow as pa
import pyarrow.parquet as pq
# records is a list of lists containing the rows of the csv
table = pa.Table.from_pylist(records)
pq.write_table(table,"sample.parquet")
Upvotes: 0
Views: 1779
Reputation: 425
Could you give an example of records? If I try tu use a list of lists as suggested fails:
>>> pa.Table.from_pylist([["1", "2"], ["first", "second"]])
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "pyarrow/table.pxi", line 3682, in pyarrow.lib.Table.from_pylist
return _from_pylist(cls=Table,
File "pyarrow/table.pxi", line 5199, in pyarrow.lib._from_pylist
names = list(mapping[0].keys())
AttributeError: 'list' object has no attribute 'keys'
I would expect records to be a list of dicts from the documentation.
data = [{'strs': '', 'floats': 4.5},
{'strs': 'foo', 'floats': 5},
{'strs': 'bar', 'floats': None}]
table = pa.Table.from_pylist(data)
You can use the schema when building the table from py_list, on this case:
schema = pa.schema([('a', pa.int64()),
('c', pa.int32()),
('d', pa.int16())
])
table = pa.Table.from_pylist(
[{'a': 1, 'b': 3}, {'a': 2, 'b': 4}, {'a': 3, 'b': 5}],
schema=schema
)
data = [{'a': 1, 'c': None, 'd': None},
{'a': 2, 'c': None, 'd': None},
{'a': 3, 'c': None, 'd': None}]
assert table.schema == schema
assert table.to_pylist() == data
Upvotes: 3